Project Summary
Alzheimer’s disease (AD) is a global crisis facing the aging population and society as a whole. With the number
of people living with AD predicted to rise dramatically in the coming decades, it is imperative to pursue research
that aims to reduce the expected incidence of dementia, such as identifying modifiable risk factors for lifestyle
interventions. A prerequisite to establishing lifestyle interventions is demonstrating a causal effect of the
proposed exposure (a risk factor) on AD or AD endophenotypes. The overarching objective of this research
program is to enhance our understanding of the causal relationships underlying Alzheimer’s disease by
utilizing genetically informed causal inference methods. We will use state-of-the-art techniques in
statistical genetics that exploit the polygenic risk scoring (PRS) and Mendelian randomization (MR)
approaches. PRS provide an estimate of an individual's genetic propensity to a trait and can be used to infer
genetic overlap between phenotypes via predicting one phenotype from the PRS of another. The first aim will
identify traits that have a shared genetic etiology with AD outcomes by conducting a phenome-wide PRS
analysis. This will prioritize putative disease-modifying traits for AD outcomes. The second aim will conduct an
MR phenome-wide association study to identify novel risk factors for AD that have not been identified using
previous epidemiological approaches, while prioritizing hypotheses identified in the current literature (e.g.
vascular health). MR uses genetic variants as proxies for exposures to provide an estimate of the causal
association between an intermediate exposure and an outcome and conceptually similar to a ‘genetic
randomized control trial’ due to the random allocation of genotypes from parents to offspring. In the final aim,
PRS and MR will be used to determine if individual risk factors differentially contribute to the development of AD
in at-risk subgroups by performing sex, ancestry, age, and APOE e4 stratified analyses to identify subgroup-
specific risk profiles and predictors. The proposed research will elucidate the risk factors underlying AD, which
will have a significant impact on the development of lifestyle interventions to prevent AD and may explain
differences in risk by sex and ancestry. Under the guidance of his mentor Dr. Alison Goate and co-mentor Dr.
Kristine Yaffe, and a team of other advisors, Dr. Andrews will pursue a rigorous training program to accomplish
the aims of this award and to develop into an independent researcher. This training will focus on developing
skills in (1) causal inference, (2) big data analytics, (3) computational genomics, and (4) professional
development. Development in these domains will be accomplished via coursework, attendance at conferences
and workshops, gaining experience in providing mentoring and leading teams, and regular feedback from his
advisory committee. Overall, the proposed study addresses a crucial and timely unmet need, and the additional
skills developed during this award will provide a strong foundation for the candidate to establish independent
leadership in the genetic epidemiology of Alzheimer’s disease.